Prognostic Significance of Proteomics‐Discovered Circulating Inflammatory Biomarkers in Patients With Pulmonary Arterial Hypertension
Bibliographic record
Abstract
BACKGROUND: Pulmonary arterial hypertension (PAH) ultimately leads to right ventricular failure and premature death. The identification of circulating biomarkers with prognostic utility is considered a priority. As chronic inflammation is recognized as key pathogenic driver, we sought to identify inflammation-related circulating proteins that add incremental value to current risk stratification models for long-term survival in patients with PAH. METHODS AND RESULTS: Plasma levels of 384 inflammatory proteins were measured with the proximity extension assay technology in patients with PAH (n=60) and controls with normal hemodynamics (n=28). Among these, 51 analytes were significantly overexpressed in the plasma of patients with PAH compared with controls. Cox proportional hazard analyses and C-statistics were performed to assess the prognostic value and the incremental prognostic value of differentially expressed proteins. A panel of 6 proteins (CRIM1 [cysteine rich transmembrane bone morphogenetic protein regulator 1], HGF [hepatocyte growth factor], FSTL3 [follistatin-like 3], PLAUR [plasminogen activator, urokinase receptor], CLSTN2 [calsyntenin 2], SPON1 [spondin 1]) were independently associated with death/lung transplantation at the time of PAH diagnosis after adjustment for the 2015 European Society of Cardiology/European Respiratory Society guidelines, the REVEAL (Registry to Evaluate Early and Long-Term PAH Disease Management) 2.0 risk scores, and the refined 4-strata risk assessment. CRIM1, PLAUR, FSTL3, and SPON1 showed incremental prognostic value on top of the predictive models. As determined by Western blot, FSTL3 and SPON1 were significantly upregulated in the right ventricle of patients with PAH and animal models (monocrotaline-injected and pulmonary artery banding-subjected rats). CONCLUSIONS: In addition to revealing new actors likely involved in cardiopulmonary remodeling in PAH, our screening identified promising circulating biomarkers to improve risk prediction in PAH, which should be externally confirmed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".